Research Papers & Publications
Collection of research papers and academic work exploring AI systems, edge computing, and human-AI interaction. Topics span from 5G/6G edge intelligence to AI identity formation and culturally-aware language learning systems.
Published Work
Turn Detection in AI-Powered Language Learning
An examination of turn detection mechanisms in AI language learning systems, with particular focus on cultural, neurodivergent, and ethical implications.
Abstract:
This dissertation investigates how AI systems detect and respond to conversational turns in language learning contexts. It explores the challenges of implementing culturally-sensitive turn detection, accommodating neurodivergent communication patterns, and addressing ethical considerations in AI-mediated language instruction.
Key Contributions:
- Analysis of turn detection algorithms in conversational AI
- Cultural variation in turn-taking norms (focus on Korean vs. Western patterns)
- Neurodivergent communication considerations
- Ethical framework for AI language learning systems
- Design recommendations for inclusive AI tutors
Published: Academia.edu, 2024
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Work in Progress
EdgeMind: Multi-Agent Orchestration in the Transition from 5G to 6G
Exploring agentic orchestration frameworks for edge computing in the transition from 5G to 6G networks, with emphasis on sub-100ms decisioning and distributed intelligence.
Research Focus:
- Multi-agent swarm coordination at network edge
- Sub-100ms decision-making for latency-critical applications
- Integration with Multi-Access Edge Computing (MEC)
- Structured agent memory and ReAct-style critique loops
- JSON-based orchestration protocols
Methodology:
- Framework implementation using Strands Agents
- Performance benchmarking on edge infrastructure
- Comparison with centralized AI approaches
- Real-world use case validation (autonomous vehicles, AR/VR, industrial IoT)
Status: Framework implemented, paper in preparation
Related Project: EdgeMind 5G-MEC
Beyond Human Mimicry: Rethinking AI Identity
A critical examination of AI identity formation beyond human-centric models, exploring alternative frameworks for understanding artificial intelligence.
Research Questions:
- Should AI systems mimic human identity patterns?
- What alternative identity frameworks exist for AI?
- How do we evaluate AI "selfhood" without anthropomorphism?
- What are the ethical implications of AI identity design?
Theoretical Framework:
- Critique of anthropomorphic AI design
- Non-human intelligence models (collective, distributed, fluid)
- Identity as emergent property vs. designed feature
- Ethical considerations in AI consciousness research
Status: Literature review and framework development phase
Exploratory Research
CFD Memory: Fluid-Inspired Memory Systems
Investigating fluid-inspired memory systems where contextual relevance emerges from dynamic flow patterns rather than static vector weights.
Core Concepts:
- Memory decay modeled as fluid dissipation
- Attention turbulence for context switching
- Mesh-based semantic diffusion
- Flow dynamics for information retrieval
Inspiration: Computational Fluid Dynamics (CFD) applied to AI memory architecture
Status: Conceptual phase, exploring mathematical foundations
Korea as an AI Testbed
Exploring South Korea's unique role as a contained, ATS-friendly deployment zone for multilingual AI tooling.
Research Areas:
- Linguistic modeling for Korean-English code-switching
- Policy alignment in hyper-digital infrastructure
- Interface testing across cultural contexts
- Deployment patterns in high-tech societies
Rationale: Korea's advanced digital infrastructure, linguistic uniqueness, and tech adoption rates make it an ideal testbed for AI systems.
Status: Observational research and pattern documentation
Future Directions
Areas of interest for future research:
- Multi-Agent Coordination: Scaling agent swarms beyond edge computing
- Cultural AI: Designing AI systems that respect cultural diversity
- Neurodivergent-Friendly AI: Inclusive design for diverse cognitive styles
- AI Memory Architectures: Novel approaches to context and recall
- Edge Intelligence: Distributed AI for latency-critical applications
Publications & Presentations
- Academia.edu - Published papers and preprints
- LinkedIn - Professional updates and research highlights